Titlebook: Markov Networks in Evolutionary Computation; Siddhartha Shakya,Roberto Santana Book 2012 Springer Berlin Heidelberg 2012 Estimation of Dis

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The Markov Network Fitness Model networks as fitness surrogates which may be used for constructing guided operators or more general hybrid algorithms.We conclude with some observations and issues which arise from work conducted in this area so far.

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Fast Fitness Improvements in Estimation of Distribution Algorithms Using Belief Propagationnd (with a low computational cost), in many scenarios, the point with the highest probability of a Bayesian network. We carry out some experiments to show how this modification can increase the potentialities of Estimation of Distribution Algorithms.

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Applications of Distribution Estimation Using Markov Network Modelling (DEUM)such as GA and Bayesian Network EDAs; trade-offs between modelling cost and reduction in search effort; and the use of MN models for surrogate evaluation.We also present guidelines for further applications and future research.